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A multivariate ordered-response model system for adults' weekday activity episode generation by activity purpose and social context

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  • Ferdous, Nazneen
  • Eluru, Naveen
  • Bhat, Chandra R.
  • Meloni, Italo

Abstract

This paper proposes a multivariate ordered-response system framework to model the interactions in non-work activity episode decisions across household and non-household members at the level of activity generation. Such interactions in activity decisions across household and non-household members are important to consider for accurate activity-travel pattern modeling and policy evaluation. The econometric challenge in estimating a multivariate ordered-response system with a large number of categories is that traditional classical and Bayesian simulation techniques become saddled with convergence problems and imprecision in estimates, and they are also extremely cumbersome if not impractical to implement. We address this estimation problem by resorting to the technique of composite marginal likelihood (CML), an emerging inference approach in the statistics field that is based on the classical frequentist approach, is very simple to estimate, is easy to implement regardless of the number of count outcomes to be modeled jointly, and requires no simulation machinery whatsoever. The empirical analysis in the paper uses data drawn from the 2007 American Time Use Survey (ATUS) and provides important insights into the determinants of adults' weekday activity episode generation behavior. The results underscore the substantial linkages in the activity episode generation of adults based on activity purpose and accompaniment type. The extent of this linkage varies by individual demographics, household demographics, day of the week, and season of the year. The results also highlight the flexibility of the CML approach to specify and estimate behaviorally rich structures to analyze inter-individual interactions in activity episode generation.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 44 (2010)
Issue (Month): 8-9 (September)
Pages: 922-943

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Handle: RePEc:eee:transb:v:44:y::i:8-9:p:922-943

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Related research

Keywords: Composite marginal likelihood (CML) approach Social interactions Activity-based modeling Multivariate ordered probit model American Time Use Survey (ATUS);

References

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Citations

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Cited by:
  1. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
  2. Nazneen Ferdous & Chandra Bhat, 2013. "A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns," Journal of Geographical Systems, Springer, vol. 15(1), pages 1-29, January.
  3. Sobhani, Anae & Eluru, Naveen & Faghih-Imani, Ahmadreza, 2013. "A latent segmentation based multiple discrete continuous extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 154-169.
  4. Smith, Michael S. & Kauermann, Göran, 2011. "Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1846-1862.
  5. Arentze, Theo A. & Ettema, Dick & Timmermans, Harry J.P., 2011. "Estimating a model of dynamic activity generation based on one-day observations: Method and results," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 447-460, February.

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